Before a new drug may be marketed to the public, the Food and Drug Administration (FDA) requires that the drug be proven safe and efficacious for its intended purpose. This required proof necessitates that extensive testing and trials of a new drug be made and the results reported to the FDA before the drug may gain regulatory approval to be marketed.
Many drugs have intended or unintended effects on the heart or cardiac function of a patient. Thus, one aspect of the proof required for regulatory approval is extensive analysis of the effect of the drug on the patient's heart, which effect is often evidenced by the morphology or shape of an electrocardiogram (ECG) obtained from the patient. A detailed analysis of the patient's ECG morphology must look to a variety of ECG signal characteristics, including those features associated with the repolarization of the heart after contraction. Features associated with heart repolarization include T-wave duration, S-T morphology, U wave, Q-T interval and heart-rate corrected Q-T interval (QTc). Anomalies in these features are, in turn, often associated with life threatening cardiac tachycardia or arrhythmias so that a main purpose for the analysis of ECG morphology data is to determine whether there is a correlation between the tested drug and life threatening tachycardia or arrhythmias.
More specifically, evidence of drug induced Torsade-de-Pointes (TdP), or torsade, is sought by analyzing the patient's ECG morphology. TdP is a type of ventricular tachycardia, or arrhythmia, characterized by fluctuation of the QRS complexes around the ECG baseline. Currently, the only indication of TdP that is accepted by regulatory authorities are features relating to an elongated Q-T interval in the ECG morphology. Regulatory authorities are thus particularly interested in any correlation between the administration of a drug and a prolongation of a patient's Q-T interval.
With the regulatory authorities currently accepting Q-T interval as the primary or only feature to predict possible drug induced TdP, two challenges are presented to pharmaceutical testing. The first challenge is to improve Q-T interval related measurements to more accurately measure the Q-T interval and the corrected Q-T Interval (QTc). The measurement of Q-T interval and the calculation of QTc are complicated by the hysteresis effect of heart rate within a heart cycle. Because of the hysteresis effect, a change in heart rate and interval between identifying features in the heartbeat waveform (the R-R interval) may not be immediately followed by a change in Q-T interval. In the field of pharmaceutical testing, it is thus desired to provide more sophisticated methods for determining when Q-T interval should be collected rather than initiating the collection responsive to the detection of an R-R interval change.
Second, it is desirable, in practice, to have the ability to collect and analyze patient data to find new morphological features which may yield a better prediction of drug induced TdP than the currently accepted Q-T interval data. However the magnitude and complexity of data that must be analyzed to identify correlative features makes this a daunting task.
Therefore, it is desirable in the field of physiological data analysis, including that involving pharmaceutical testing, to develop a method for processing raw ECG data collected from drug trial subjects and for analyzing many ECG morphological features to identify complex correlations that are indicative of TdP or other drug induced adverse effects, such as arrhythmia.